Linked Data for Improved Vaccine Information Systems

https://w3id.org/vacseen SWAT4LS, 8th December 2015, Cambridge
Getting VacSeen-ated: Linked Data for Improved
Vaccine Information Systems
Monika Solanki
https://w3id.org/people/msolanki
@nimonika
University of Oxford
Joint work with
Partha S Bhattacharjee, Rahul Bhattacharyya, Isaac Ehrenberg,
Sanjay Sarma
Auto ID Labs, MIT

Motivation
The expansion of vaccine programs globally...
monika.solanki@cs.ox.ac.uk, @nimonika Linked Data for Improved Vaccine Information Systems

Motivation
...has accentuated challenges for governments...
Most developing countries are not equipped to efﬁciently store,
track, and transport increased vaccine volumes

Motivation
...and manufacturers
Lack of visibility and control over supply chain
Limited ability for demand forecasting
Exposure to counterfeiting and diversion of products
Limited ability to cope with regulatory developments

Motivation
Several approaches are under development to address the vaccine
access challenge

Motivation
Observations
Despite improved information ﬂow, issues about
interoperability and at-scale last mile tracking continue to
persist.
Several studies have reported the effectiveness of using
barcodes in tracking vaccine consumption.

Motivation
Our research focuses on the Information Technology dimension

Contributions
Demonstrate the utility of VacSeen in authenticating
barcode scans and generating attendant rich contextual
information.
Geolocate and classify the scans based on whether or not
they were recorded by authorized personnel using
authenticated devices.
Exploit multiple data sources: mobile applications, barcode
databases, healthcare provider databases and LOD cloud.
Two (mobile/Android) applications: generate biomedical
factsheets about the vaccines, identifying nearest airport to
a selected scan location.

VacSeen: Process ﬂow
Mobile-based barcode scans on the ﬁeld are retrospectively validated
using a data lake formed from logistical and health information
systems

VacSeen: Knowledge representation
EEM*: The EPCIS Event Model
Vaccine transaction events as abstractions for traceability.
Focuses on a tight conformance with the EPCIS 1.1*
standard and Simplicity.
EEM has been mapped* to PROV-O*.
*http://purl.org/eem#
*http://www.w3.org/ns/prov#
*http://www.gs1.org/epcis
*http://fispace.aston.ac.uk/ontologies/eem_prov.html
M. Solanki et al. EPCIS event-based traceability in pharmaceutical supply
chains via automated generation of linked pedigrees. ISWC 2014

EEM modules
Temporal
time of occurrence
time of record
timezone offset
BusinessAction
Disposition
Business step
Transaction
Product
EPC
EPCClass
Aggregation Identifiers
Input/Output Quantity List
Spatial
ReadPoint Location
Business Location
Source
Destination
EPCIS Event
Object Event
AggregationEvent
TransactionEvent
TransformationEvent
QuantityEvent*
* Deprecated in EPCIS 1.1
Structure of EEM
Sensors
EPC Readers
GoodRelations,
Collections
DUL
Semantic Sensor Network
Ontology
wgs84, vCard
DUL
CBVVocab
PROV-O
EPCISException
Hierarchy of EPCISException

VacSeen1*
The VacSeen1 ontology uses and extends EEM to model barcode
scan, product, and personnel data
Extended with existing, well known ontologies to fully
address the needs of the project.
Light-weight ontology with just enough formalization to
enable detailed querying.
Minimal rules to avoid issues pertaining to inferencing.
*http://www.violinet.org/vaccineontology/

Important steps
Generation of persistent URIs
Using ontology classes in RDB-RDF translation
Next steps
Making URIs dereferenceable
Using classes from Vaccine Ontology and Vaccine Adverse
Event Ontology for new applications

VacSeen: RDB→RDF using D2RQ
While R2RML is the standard for RDB→RDF translation,
D2RQ is used because of its similarity with RDF, extensive
support, and compatibility with the former.
Logically closer to RDF than RDB compared to R2RML
resulting in relatively less complex queries.
Supports standards such as R2RML.
Extensively used and well documented.

VacSeen: RDB→RDF using D2RQ
Important steps
Customization of mapping ﬁle using ontology terms.
Enforcement of integrity constraints on data by specifying
integrity constraints in the mapping ﬁle.

VacSeen: Data storage
Triplestore: GraphDB-Lite over Sesame
Graphical Interface for implementation by less technical
users.
Freely available.
DL and rule-based reasoning support.
Multiple options for storage, access, and querying.
Datasets loaded and used: vaccine data, healthcare system
data, and barcode scan data.

VacSeen: Typical SPARQL queries
Latitude, Longitude, operatorID, deviceID of scan events where the
GTIN scanned exists in the sc_data database, the operator ID exists
in the scan_operator table, and the device ID exists in the
scan_device table
Query using EEM & VacSeen1
SELECT DISTINCT ?EPCISEvent ?GTIN ?operatorID ?deviceID ?latitude ?longitude
WHERE
{
?EPCISEvent a eem:EPCISEvent.
?EPCISEvent vacseen1:ScanID ?scanID.
?EPCISEvent eem:EPCNumber ?GTIN.
?s vacseen1:sc_data_GTIN ?GTIN.
?EPCISEvent vacseen1:scan_event_operatorID ?operatorID.
?scanOperator vacseen1:scan_operator_OperatorID ?operatorID.
?EPCISEvent vacseen1:scan_event_deviceID ?deviceID.
?scanDevice vacseen1:scan_device_DeviceID ?deviceID.
?EPCISEvent vacseen1:LatitudeOfBarcodeScanEvent ?latitude.
FILTER(?latitude > ’0.0’).
?EPCISEvent vacseen1:LongitudeOfBarcodeScanEvent ?longitude.
}

VacSeen: Typical SPARQL queries
Data about Rotavirus vaccine from DBpedia
INSERT{?s ?p ?o}
WHERE
{
SERVICE <http://dbpedia.org/sparql>
{
{
:Rotavirus_vaccine ?p ?o.
BIND(:Rotavirus_vaccine AS ?s)
}
UNION
{
?s ?p :Rotavirus_vaccine.
BIND(:Rotavirus_vaccine AS ?o)
}
}
}

VacSeen: Data storage
While it is easy to get started with Sesame and do routine operations,
issues can arise when using plug-ins
Challenges
Issues with “jsonp callbacks” because of incompatibility of GraphDB-Lite with recent releases of Sesame.
Absence of access to SPARQL lifting because of aforementioned incompatibility
Absent GraphDB customer-support for non-paying users
Resolution
Sesame mailing lists
Replacement of jar ﬁles as a temporary measure
Permanent solution through replacement of jsonp callback with CORS headers for cross-domain access

VacSeen: Exploiting the LOD cloud
Two applications:
Creating biomedical factsheets about vaccines using Dbpedia.
Identifying nearest airports to every scan location for logistical
planning.

VacSeen: Scan Authentication
Provides additional context for each barcode scan to get a
deeper understanding about vaccine handling operations.

VacSeen: Next steps
Future work will focus on developing more advanced Linked
Data-based applications that leverage large scale and secure data

Linked Data for Improved Vaccine Information Systems

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